Genomics & Informatics

  • 제15권4호
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  • Pages.156-161
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  • 2017
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  • 1598-866X(pISSN)
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  • 2234-0742(eISSN)
한국유전체학회 (Korea Genome Organization)
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Classification of Genes Based on Age-Related Differential Expression in Breast Cancer

  • Lee, Gunhee (Department of Biological Science, Sangji University) ;
  • Lee, Minho (Catholic Precision Medicine Research Center, College of Medicine, The Catholic University of Korea)
  • 투고 : 2017.11.28
  • 심사 : 2017.12.03
  • 발행 : 2017.12.31
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초록

Transcriptome analysis has been widely used to make biomarker panels to diagnose cancers. In breast cancer, the age of the patient has been known to be associated with clinical features. As clinical transcriptome data have accumulated significantly, we classified all human genes based on age-specific differential expression between normal and breast cancer cells using public data. We retrieved the values for gene expression levels in breast cancer and matched normal cells from The Cancer Genome Atlas. We divided genes into two classes by paired t test without considering age in the first classification. We carried out a secondary classification of genes for each class into eight groups, based on the patterns of the p-values, which were calculated for each of the three age groups we defined. Through this two-step classification, gene expression was eventually grouped into 16 classes. We showed that this classification method could be applied to establish a more accurate prediction model to diagnose breast cancer by comparing the performance of prediction models with different combinations of genes. We expect that our scheme of classification could be used for other types of cancer data.

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참고문헌

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피인용 문헌

  1. An Efficient Feature Selection Strategy Based on Multiple Support Vector Machine Technology with Gene Expression Data vol.2018, pp.2314-6141, 2018, https://doi.org/10.1155/2018/7538204